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Edward William Reutzel

 https://orcid.org/0000-0002-7832-4692
    • 626 Citations
    • 14 h-Index
    20012019
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    Fingerprint Dive into the research topics where Edward William Reutzel is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

    • 11 Similar Profiles
    3D printers Engineering & Materials Science
    Lasers Engineering & Materials Science
    Welding Engineering & Materials Science
    Processing Engineering & Materials Science
    Fusion reactions Engineering & Materials Science
    Geometry Engineering & Materials Science
    Powders Chemical Compounds
    Laser beam welding Engineering & Materials Science

    Network Recent external collaboration on country level. Dive into details by clicking on the dots.

    Research Output 2001 2019

    Deep learning of variant geometry in layerwise imaging profiles for additive manufacturing quality control

    Imani, F., Chen, R., Diewald, E., Reutzel, E. W. & Yang, H., Nov 1 2019, In : Journal of Manufacturing Science and Engineering, Transactions of the ASME. 141, 11, 111001.

    Research output: Contribution to journal › Article

    3D printers
    Quality control
    Imaging techniques
    Geometry
    Defects
    12 Citations (Scopus)

    Effect of processing conditions on the microstructure, porosity, and mechanical properties of Ti-6Al-4V repair fabricated by directed energy deposition

    Kistler, N. A., Corbin, D., Nassar, A. R., Reutzel, E. W. & Beese, A. M., Feb 1 2019, In : Journal of Materials Processing Technology. 264, p. 172-181 10 p.

    Research output: Contribution to journal › Article

    Repair
    Porosity
    Mechanical properties
    Microstructure
    Substrates
    1 Citation (Scopus)

    Formation processes for large ejecta and interactions with melt pool formation in powder bed fusion additive manufacturing

    Nassar, A. R., Gundermann, M. A., Reutzel, E. W., Guerrier, P., Krane, M. H. & Weldon, M. J., Dec 1 2019, In : Scientific reports. 9, 1, 5038.

    Research output: Contribution to journal › Article

    Open Access
    Powders
    Particle Size
    Lasers
    Behavior Observation Techniques
    13 Citations (Scopus)

    Application of supervised machine learning for defect detection during metallic powder bed fusion additive manufacturing using high resolution imaging.

    Gobert, C., Reutzel, E. W., Petrich, J., Nassar, A. R. & Phoha, S., May 1 2018, In : Additive Manufacturing. 21, p. 517-528 12 p.

    Research output: Contribution to journal › Article

    3D printers
    Powders
    Tomography
    Learning systems
    Fusion reactions

    Build height control in directed energy deposition using a model-based feed-forward controller

    Wang, Q., Li, J., Nassar, A. R., Reutzel, E. W. & Mitchell, W., Jan 1 2018, Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems. American Society of Mechanical Engineers (ASME), (ASME 2018 Dynamic Systems and Control Conference, DSCC 2018; vol. 2).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Controllers
    Feedback
    Lasers
    Time measurement
    3D printers